Adipocyte-specific Beclin1 deletion impairs lipolysis and mitochondrial integrity in adipose tissue.

OBJECTIVE: Beclin1 is a core molecule of the macroautophagy machinery. Although dysregulation of macroautophagy is known to be involved in metabolic disorders, the function of Beclin1 in adipocyte metabolism has not been investigated. In the present study, we aimed to study the role of Beclin1 in lipolysis and mitochondrial homeostasis of adipocytes. METHODS: Autophagic flux during lipolysis was examined in adipocytes cultured in vitro and in the adipose tissue of mice. Adipocyte-specific Beclin1 knockout (KO) mice were used to investigate the activities of Beclin1 in adipose tissues. RESULTS: cAMP/PKA signaling increased the autophagic flux in adipocytes differentiated from C3H10T1/2 cells. In vivo autophagic flux was higher in the brown adipose tissue (BAT) than that in the white adipose tissue and was further increased by the ß3 adrenergic receptor agonist CL316243. In addition, surgical denervation of BAT greatly reduced autophagic flux, indicating that sympathetic nerve activity is a major regulator of tissue autophagy. Adipocyte-specific KO of Beclin1 led to a hypertrophic enlargement of lipid droplets in BAT and impaired CL316243-induced lipolysis/lipid mobilization and energy expenditure. While short-term effects of Beclin1 deletion were characterized by an increase in mitochondrial proteins, long-term Beclin1 deletion led to severe disruption of autophagy, resulting in mitochondrial loss, and dramatically reduced the expression of genes involved in lipid metabolism. Consequently, adipose tissue underwent increased activation of cell death signaling pathways, macrophage recruitment, and inflammation, particularly in BAT. CONCLUSIONS: The present study demonstrates the critical roles of Beclin1 in the maintenance of lipid metabolism and mitochondrial homeostasis in adipose tissues.

Sperm RNA elements as markers of health.

Idiopathic infertility, an etiology not identified as part of standard clinical assessment, represents approximately 20% of all infertility cases. Current male infertility diagnosis focuses on the concentration, motility, and morphology of spermatozoa. This is of limited value when predicting birth success and of limited utility when selecting the optimum treatment. At fertilization, spermatozoa provide their genomic contribution, as well as a set of RNAs and proteins that have distinct roles in development. The potential of spermatozoal RNAs to be used as a prognostic of live birth has been shown [Jodar et al. (2015) Science Translational Medicine 7(295):295re6]. This relied on a set of 648 sperm RNA elements derived from 285 genes that are perhaps indicative of future health status. To address this tenet, the present study correlated the levels of each transcript among all samples to assess linkage between transcript absence, birth success, and possible disease association. Correlations between transcript levels of the 285 genes were analyzed amongst themselves, and within the context of the entire transcript population for these samples. The transcripts ACE, GIGYF2, and ODF2 had many negative correlations and form the majority of correlations, suggesting an important function for these transcripts. Eleven of the 285 queried genes had disease-associated variants within a sperm RNA element. Three genes, GPX4, NDRG1, and RPS24 had SREs were absent in at least one individual from the test cohort. GPX4 and RPS24 are associated with developmental defects and/or neonatal lethality. This leaves the intriguing possibility that, while sperm RNAs delivered to the oocyte inform the success of live birth, they may also be predictors of human health. ABBREVIATIONS: GO: Gene Ontology; ART: assisted reproductive technology; IVF: in vitro fertilization; ICSI: intra-cytoplasmic sperm injection; RNA-seq: RNA-sequencing; TIC: timed intercourse; IUI: intrauterine insemination; SRE: sperm RNA elements; HPA: Human Protein Atlas; SMDS: sedaghatian-type spondylometaphyseal dysplasia; DBA: Diamond-Blackfan anemia; RPKM: reads per kilobase per million; TPM: transcripts per million; IPA: Ingenuity Pathway Analysis; OMIM: Online Mendelian Inheritance in Man.